文章基本信息

标题：Rmixmod: The R Package of the Model-Based Unsupervised, Supervised, and Semi-Supervised Classification Mixmod Library
本地全文：下载
作者：Rémi Lebret ; Serge Iovleff ; Florent Langrognet 等
期刊名称：Journal of Statistical Software
印刷版ISSN：1548-7660
电子版ISSN：1548-7660
出版年度：2015
卷号：67
期号：1
页码：1-29
语种：English
出版社：University of California, Los Angeles
摘要：Mixmod is a well-established software package for fitting mixture models of multivariate Gaussian or multinomial probability distribution functions to a given dataset with either a clustering, a density estimation or a discriminant analysis purpose. The Rmixmod S4 package provides an interface from the R statistical computing environment to the C++ core library of Mixmod (mixmodLib). In this article, we give an overview of the model-based clustering and classification methods implemented, and we show how the R package Rmixmod can be used for clustering and discriminant analysis.
关键词：model-based clustering;discriminant analysis;classification;visualisation;R;Rmixmod